Search results for: fuzzy numbers
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1853

Search results for: fuzzy numbers

1283 Lung Cancer Patients in Eastern Region of Nepal

Authors: Ram Sharan Mehta

Abstract:

The number of new cancer cases annually is estimated to rise from 10.9 million in 2002 to more than 16 million by 2020, if current trends continue. Much of this increase in absolute numbers derives from the ageing of populations worldwide. The objectives of this study were to find out the demographic characteristics of the admitted cancer patients in BPKIHS. It was hospital based descriptive cross-sectional study conducted reviewing all the records of admitted diagnosed cancer patients in BPKIHS from 15th October 2004 to 14th October 2012. Using total enumerative sampling technique all 1379 diagnosed cancer patients record were reviewed after obtaining the permission from concerned authorities. Using SPSS-15 software package data was analyzed. It was found that majority (71%) of cancer patients were of age more than 40 years and equal of both sexes. Most of the clients were form Sunsari (31.1%), Morang (16.6%) and Jhapa (17%) districts. The mean hospitalization day is 8.32 and very few patients (5.2%) were only cured. The numbers of cancer patients are markedly increases in BPKIHS, especially in advanced stage. It is mandatory to start the cancer information and education programme in eastern region of Nepal and proper management of cancer patients using chemotherapy, radiotherapy and surgery at BPKIHS for quality patient care.

Keywords: lung, cancer, patients, Nepal

Procedia PDF Downloads 354
1282 Interaction or Conflict: Addressing Modern Trans-Himalayan Pastoralism and Wildlife

Authors: Amit Kaushik

Abstract:

Equus kiang kiang is an indigenous large-bodied herbivore species, and in India, it is restricted to limited geographies of Ladakh. One of such areas is the Tsokar Basin. With the rise in global pashmina demand, the livestock numbers have grown significantly. Previous studies have reported conflict between a nomadic pastoral community, the Changpas, and kiang. Absentee pastoralism (in lieu of pure pastoralism) and tourism are two major economic activities among the local people. However, the social, economic, political, and ecological changes are inevitable in such a contemporary system. The study examines several factors influencing the local pastoral economy and focuses on the presence of two non-human cohabitants, kiang, and the wolf. This study used semi-structured interviews and vehicle count method in four different seasons. The results show that people perceived kiang as a threat but also reveal a level of tolerance towards them. The locals predicted high kiang numbers ranging from 200-3000 in the basin and contrastingly ranked them behind wolves, which are very few in numbers. Due to a lack of scientific pieces of evidence, the kiang population status remains obscure, and local peoples’ concerns remain unaddressed. But how this competitive dysfunctionality does take place? On one side, the rural development or the animal husbandry department aims at developing the area by providing stall-feed and tourism, whereas, on another side, the wildlife department emphasizes wildlife conservation. Therefore, the managers and planners may need to be cautious about the local socio-ecological complexities and may require inter-departmental communications. The study concludes that an interdisciplinary inquiry may be an important tool in understanding such a precarious situation and may be used in the policy-making processes.

Keywords: coexistence, human-livestock-wildlife interactions, interdisciplinary approach, kiang, policymaking, tsokar.

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1281 Active Islanding Detection Method Using Intelligent Controller

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

Abstract:

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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1280 Prioritization in a Maintenance, Repair and Overhaul (MRO) System Based on Fuzzy Logic at Iran Khodro (IKCO)

Authors: Izadi Banafsheh, Sedaghat Reza

Abstract:

Maintenance, Repair, and Overhaul (MRO) of machinery are a key recent issue concerning the automotive industry. It has always been a debated question what order or priority should be adopted for the MRO of machinery. This study attempts to examine several criteria including process sensitivity, average time between machine failures, average duration of repair, availability of parts, availability of maintenance personnel and workload through a literature review and experts survey so as to determine the condition of the machine. According to the mentioned criteria, the machinery were ranked in four modes below: A) Need for inspection, B) Need for minor repair, C) Need for part replacement, and D) Need for major repair. The Fuzzy AHP was employed to determine the weighting of criteria. At the end, the obtained weights were ranked through the AHP for each criterion, three groups were specified: shaving machines, assembly and painting in four modes. The statistical population comprises the elite in the Iranian automotive industry at IKCO covering operation managers, CEOs and maintenance professionals who are highly specialized in MRO and perfectly knowledgeable in how the machinery function. The information required for this study were collected from both desk research and field review, which eventually led to construction of a questionnaire handed out to the sample respondents in order to collect information on the subject matter. The results of the AHP for weighting the criteria revealed that the availability of maintenance personnel was the top priority at coefficient of 0.206, while the process sensitivity took the last priority at coefficient of 0.066. Furthermore, the results of TOPSIS for prioritizing the IKCO machinery suggested that at the mode where there is need for inspection, the assembly machines took the top priority while paining machines took the third priority. As for the mode where there is need for minor repairs, the assembly machines took the top priority while the third priority belonged to the shaving machines. As for the mode where there is need for parts replacement, the assembly machines took the top priority while the third belonged to the paining machinery. Finally, as for the mode where there is need for major repair, the assembly machines took the top priority while the third belonged to the paining machinery.

Keywords: maintenance, repair, overhaul, MRO, prioritization of machinery, fuzzy logic, AHP, TOPSIS

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1279 Prioritization Assessment of Housing Development Risk Factors: A Fuzzy Hierarchical Process-Based Approach

Authors: Yusuf Garba Baba

Abstract:

The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: risk management, risk identification, risk analysis, analytic hierarchical process

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1278 Stability Analysis of Endemic State of Modelling the Effect of Vaccination and Novel Quarantine-Adjusted Incidence on the Spread of Newcastle Disease Virus

Authors: Nurudeen Oluwasola Lasisi, Abdulkareem Afolabi Ibrahim

Abstract:

Newcastle disease is an infection of domestic poultry and other bird species with virulent Newcastle disease virus (NDV). In this paper, we study the dynamics of modeling the Newcastle disease virus (NDV) using a novel quarantine-adjusted incidence. We do a comparison of Vaccination, linear incident rate, and novel quarantine adjusted incident rate in the models. The dynamics of the models yield disease free and endemic equilibrium states. The effective reproduction numbers of the models are computed in order to measure the relative impact for the individual bird or combined intervention for effective disease control. We showed the local and global stability of endemic equilibrium states of the models, and we found that stability of endemic equilibrium states of models are globally asymptotically stable if the effective reproduction numbers of the models equations are greater than a unit.

Keywords: effective reproduction number, endemic state, mathematical model, Newcastle disease virus, novel quarantine-adjusted incidence, stability analysis

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1277 Comparison Analysis of Fuzzy Logic Controler Based PV-Pumped Hydro and PV-Battery Storage Systems

Authors: Seada Hussen, Frie Ayalew

Abstract:

Integrating different energy resources, like solar PV and hydro, is used to ensure reliable power to rural communities like Hara village in Ethiopia. Hybrid power system offers power supply for rural villages by providing an alternative supply for the intermittent nature of renewable energy resources. The intermittent nature of renewable energy resources is a challenge to electrifying rural communities in a sustainable manner with solar resources. Major rural villages in Ethiopia are suffering from a lack of electrification, that cause our people to suffer deforestation, travel for long distance to fetch water, and lack good services like clinic and school sufficiently. The main objective of this project is to provide a balanced, stable, reliable supply for Hara village, Ethiopia using solar power with a pumped hydro energy storage system. The design of this project starts by collecting data from villages and taking solar irradiance data from NASA. In addition to this, geographical arrangement and location are also taken into consideration. After collecting this, all data analysis and cost estimation or optimal sizing of the system and comparison of solar with pumped hydro and solar with battery storage system is done using Homer Software. And since solar power only works in the daytime and pumped hydro works at night time and also at night and morning, both load will share to cover the load demand; this need controller designed to control multiple switch and scheduling in this project fuzzy logic controller is used to control this scenario. The result of the simulation shows that solar with pumped hydro energy storage system achieves good results than with a battery storage system since the comparison is done considering storage reliability, cost, storage capacity, life span, and efficiency.

Keywords: pumped hydro storage, solar energy, solar PV, battery energy storage, fuzzy logic controller

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1276 Analysis and Suggestion on Patent Protection in Shanghai, China

Authors: Yuhong Niu, Na Li, Chunlin Jin, Hansheng Ding

Abstract:

The study reviewed all types of patents applied by Shanghai health system to analyze how patent development in China from the year of 1990 to 2012. The study used quantitative and comparative analysis to investigate the change and trends of patent numbers, patent types, patent claims, forward citations, patent life, patent transactions, etc. Results reflected an obviously increased numbers of invention patents, applications, and authorizations and short-life patents, but the ratio of invention patents represented an up and down change. Forward citations and transactions ratio always kept at a low level. The results meant that the protection of intellectual property in the Shanghai health sector had made great progress and lots of positive changes due to incentive policies by local government. However, the low-quality patents, at the same time, increased rapidly. Thus, in the future, it is suggested that the quality management should be strengthened, and invents should be estimated before patent application. It is also suggested that the incentives for intellectual property should be optimized to promote the comprehensive improvement of patent quantity and quality.

Keywords: patent claims, forward citations, patent life, patent transactions ratio

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1275 Coupled Space and Time Homogenization of Viscoelastic-Viscoplastic Composites

Authors: Sarra Haouala, Issam Doghri

Abstract:

In this work, a multiscale computational strategy is proposed for the analysis of structures, which are described at a refined level both in space and in time. The proposal is applied to two-phase viscoelastic-viscoplastic (VE-VP) reinforced thermoplastics subjected to large numbers of cycles. The main aim is to predict the effective long time response while reducing the computational cost considerably. The proposed computational framework is a combination of the mean-field space homogenization based on the generalized incrementally affine formulation for VE-VP composites, and the asymptotic time homogenization approach for coupled isotropic VE-VP homogeneous solids under large numbers of cycles. The time homogenization method is based on the definition of micro and macro-chronological time scales, and on asymptotic expansions of the unknown variables. First, the original anisotropic VE-VP initial-boundary value problem of the composite material is decomposed into coupled micro-chronological (fast time scale) and macro-chronological (slow time-scale) problems. The former is purely VE, and solved once for each macro time step, whereas the latter problem is nonlinear and solved iteratively using fully implicit time integration. Second, mean-field space homogenization is used for both micro and macro-chronological problems to determine the micro and macro-chronological effective behavior of the composite material. The response of the matrix material is VE-VP with J2 flow theory assuming small strains. The formulation exploits the return-mapping algorithm for the J2 model, with its two steps: viscoelastic predictor and plastic corrections. The proposal is implemented for an extended Mori-Tanaka scheme, and verified against finite element simulations of representative volume elements, for a number of polymer composite materials subjected to large numbers of cycles.

Keywords: asymptotic expansions, cyclic loadings, inclusion-reinforced thermoplastics, mean-field homogenization, time homogenization

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1274 Management of Jebusaea hammerschmidtii and Batrachedra amydraula on Date Palm Trees in UAE

Authors: Mohammad Ali Al-Deeb, Hamda Ateeq Al Dhaheri

Abstract:

Insects cause major damage to crops and fruit trees worldwide. In the United Arab Emirates, the date palm tree is the most economically important tree which is used for date production as well as an ornamental tree. In 2002, the number of date palm trees in UAE was 40,700,000 and it is increasing over time. The longhorn stem borer (Jebusaea hammerschmidtii) and the lesser date month (Batrachedra amydraula) are important insect pests causing damage to date palm trees in UAE. Population dynamics of the Jebusaea hammerschmidtii and Batrachedra amydraula were studied by using light and pheromons traps, respectively in Al-Ain, UAE. The first trap catch of B. amydraula adults occurred on 19 April and the insect population peaked up on 26 April 2014. The first trap catch of J. hammerschmidtii occurred in April 2014. The numbers increased over time and the population peak occurred in June. The trapping was also done in 2015. The changes in insect numbers in relation to weather parameters are discussed. Also, the importance of the results on the management of these two pests is highlighted.

Keywords: date palm, integrated pest management, UAE, light trap, pheromone trap

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1273 Unsupervised Detection of Burned Area from Remote Sensing Images Using Spatial Correlation and Fuzzy Clustering

Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

Abstract:

Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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1272 Clustering Locations of Textile and Garment Industries to Compare with the Future Industrial Cluster in Thailand

Authors: Kanogkan Leerojanaprapa

Abstract:

Textile and garment industry is used to a major exporting industry of Thailand. According to lacking of the nation's price-competitiveness by stopping the EU's GSP (Generalised Scheme of Preferences) and ‘Nationwide Minimum Wage Policy’ that Thailand’s employers must pay all employees at least 300 baht (about $10) a day, the supply chains of the Thai textile and garment industry is affected and need to be reformed. Therefore, either Thai textile or garment industry will be existed or not would be concerned. This is also challenged for the government to decide which industries should be promoted the future industries of Thailand. Recently Thai government launch The Cluster-based Special Economic Development Zones Policy for promoting business cluster (effect on September 16, 2015). They define a cluster as the concentration of interconnected businesses and related institutions that operate within the same geographic areas and textiles and garment is one of target industrial clusters and 9 provinces are targeted (Bangkok, Kanchanaburi, Nakhon Pathom, Ratchaburi, Samut Sakhon, Chonburi, Chachoengsao, Prachinburi, and Sa Kaeo). The cluster zone are defined to link west-east corridor connected to manufacturing source in Cambodia and Mynmar to Bangkok where are promoted to be design, sourcing, and trading hub. The Thai government will provide tax and non-tax incentives for targeted industries within the clusters and expects these businesses are scattered to where they can get the most benefit which will identify future industrial cluster. This research will show the difference between the current cluster and future cluster following the target provinces of the textile and garment. The current cluster is analysed from secondary data. The four characteristics of the numbers of plants in Spinning, weaving and finishing of textiles, Manufacture of made-up textile articles, except apparel, Manufacture of knitted and crocheted fabrics, and Manufacture of other textiles, not elsewhere classified in particular 77 provinces (in total) are clustered by K-means cluster analysis and Hierarchical Cluster Analysis. In addition, the cluster can be confirmed and showed which variables contribute the most to defined cluster solution with ANOVA test. The results of analysis can identify 22 provinces (which the textile or garment plants are located) into 3 clusters. Plants in cluster 1 tend to be large numbers of plants which is only Bangkok, Next plants in cluster 2 tend to be moderate numbers of plants which are Samut Prakan, Samut Sakhon and Nakhon Pathom. Finally plants in cluster 3 tend to be little numbers of plants which are other 18 provinces. The same methodology can be implemented in other industries for future study.

Keywords: ANOVA, hierarchical cluster analysis, industrial clusters, K -means cluster analysis, textile and garment industry

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1271 Effect of Tilt Angle of Herringbone Microstructures on Enhancement of Heat and Mass Transfer

Authors: Nathan Estrada, Fangjun Shu, Yanxing Wang

Abstract:

The heat and mass transfer characteristics of a simple shear flow over a surface covered with staggered herringbone structures are numerically investigated using the lattice Boltzmann method. The focus is on the effect of ridge angle of the structures on the enhancement of heat and mass transfer. In the simulation, the temperature and mass concentration are modeled as a passive scalar released from the moving top wall and absorbed at the structured bottom wall. Reynolds number is fixed at 100. Two Prandtl or Schmidt numbers, 1 and 10, are considered. The results show that the advective scalar transport plays a more important role at larger Schmidt numbers. The fluid travels downward with higher scalar concentration into the grooves at the backward grove tips and travel upward with lower scalar concentration at the forward grove tips. Different tile angles result in different flow advection in wall-normal direction and thus different heat and mass transport efficiencies. The maximum enhancement is achieved at an angle between 15o and 30o. The mechanism of heat and mass transfer is analyzed in detail.

Keywords: fluid mechanics, heat and mass transfer, microfluidics, staggered herringbone mixer

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1270 The Development of Leisure and Endowment Characteristic Villages in the Perspective of Balancing the Dwellers and Aged Visitors:A Case Study of Villages in Hangzhou Metropolitan Area

Authors: Zijiao Chai, Wangming Li

Abstract:

Under the background of increasing aging population, the situation of city endowment resources shortage gradually revealed. And many villages in the metropolitan area with the good natural ecological environment and leisure tourism base, have become one of the main destinations of urban old people for the off-site pension. This paper is based on a survey of more than ten villages which are characterized by leisure and endowment in Hangzhou metropolitan area, China. The satisfaction degree of the two main groups in the villages, dwellers, and aged visitors, is researched using the method of fuzzy comprehensive evaluation. The statistics are obtained from 535 questionnaires and qualitative interview. According to the satisfaction scores, it could be determined whether the dwellers and aged visitors have reached the equilibrium state. The equilibrium state is the development target of the villages, and it`s defined by environmentally friendly, proper for employment and pension, facilities sharing and harmonious life for each other. Furthermore, this paper comes up with some planning countermeasures in order to avoid "imbalance between dwellers and aged visitors" and obtain sustainable development while maintaining the economic benefit.

Keywords: aged visitors, balance between dwellers and aged visitors, dwellers, fuzzy comprehensive evaluation, Hangzhou metropolitan area, leisure and endowment characteristic villages

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1269 A High Efficiency Reduced Rules Neuro-Fuzzy Based Maximum Power Point Tracking Controller for Photovoltaic Array Connected to Grid

Authors: Lotfi Farah, Nadir Farah, Zaiem Kamar

Abstract:

This paper achieves a maximum power point tracking (MPPT) controller using a high-efficiency reduced rules neuro-fuzzy inference system (HE2RNF) for a 100 kW stand-alone photovoltaic (PV) system connected to the grid. The suggested HE2RNF based MPPT seeks the optimal duty cycle for the boost DC-DC converter, making the designed PV system working at the maximum power point (MPP), then transferring this power to the grid via a three levels voltage source converter (VSC). PV current variation and voltage variation are chosen as HE2RNF-based MPPT controller inputs. By using these inputs with the duty cycle as the only single output, a six rules ANFIS is generated. The high performance of the proposed HE2RNF numerically in the MATLAB/Simulink environment is shown. The 0.006% steady-state error, 0.006s of tracking time, and 0.088s of starting time prove the robustness of this six reduced rules against the widely used twenty-five ones.

Keywords: PV, MPPT, ANFIS, HE2RNF-based MPPT controller, VSC, grid connection

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1268 Calibrating Risk Factors for Road Safety in Low Income Countries

Authors: Atheer Al-Nuaimi, Harry Evdorides

Abstract:

Daily, many individuals die or get harmed on streets around the globe, which requires more particular solutions for transport safety issues. International road assessment program (iRAP) is one of the models that are considering many variables which influence road user’s safety. In iRAP, roads have been partitioned into five-star ratings from 1 star (the most reduced level) to 5 star (the most noteworthy level). These levels are calculated from risk factors which represent the effect of the geometric and traffic conditions on rod safety. The result of iRAP philosophy are the countermeasures that can be utilized to enhance safety levels and lessen fatalities numbers. These countermeasures can be utilized independently as a single treatment or in combination with other countermeasures for a section or an entire road. There is a general understanding that the efficiency of a countermeasure is liable to reduction when it is used in combination with various countermeasures. That is, crash diminishment estimations of single countermeasures cannot be summed easily. In the iRAP model, the fatalities estimations are calculated using a specific methodology. However, this methodology suffers overestimations. Therefore, this study has developed a calibration method to estimate fatalities numbers more accurately.

Keywords: crash risk factors, international road assessment program, low-income countries, road safety

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1267 Training a Neural Network to Segment, Detect and Recognize Numbers

Authors: Abhisek Dash

Abstract:

This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

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1266 The Fuzzy Logic Modeling of Performance Driver Seat’s Localised Cooling and Heating in Standard Car Air Conditioning System

Authors: Ali Ates, Sadık Ata, Kevser Dincer

Abstract:

In this study, performance of the driver seat‘s localized cooling and heating in a standard car air conditioning system was experimentally investigated and modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Climate function at automobile is an important variable for thermal comfort. In the experimental study localized heating and cooling performances have been examined with the aid of a mechanism established to a vehicle. The equipment’s used in the experimental setup/mechanism have been provided and assembled. During the measurement, the status of the performance level has been determined. Input parameters revolutions per minute and time; output parameters car seat cooling temperature, car back cooling temperature, car seat heating temperature, car back heating temperature were described by RBMTF if-the rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF could be successfully used in standard car air conditioning system.

Keywords: air conditioning system, cooling-heating, RMBTF modelling, car seat

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1265 A Comparison of South East Asian Face Emotion Classification based on Optimized Ellipse Data Using Clustering Technique

Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

Abstract:

In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

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1264 Analysis of Heat Transfer in a Closed Cavity Ventilated Inside

Authors: Benseghir Omar, Bahmed Mohamed

Abstract:

In this work, we presented a numerical study of the phenomenon of heat transfer through the laminar, incompressible and steady mixed convection in a closed square cavity with the left vertical wall of the cavity is subjected to a warm temperature, while the right wall is considered to be cold. The horizontal walls are assumed adiabatic. The governing equations were discretized by finite volume method on a staggered mesh and the SIMPLER algorithm was used for the treatment of velocity-pressure coupling. The numerical simulations were performed for a wide range of Reynolds numbers 1, 10, 100, and 1000 numbers are equal to 0.01,0.1 Richardson, 0.5,1 and 10.The analysis of the results shows a flow bicellular (two cells), one is created by the speed of the fan placed in the inner cavity, one on the left is due to the difference between the temperatures right wall and the left wall. Knowledge of the intensity of each of these cells allowed us to get an original result. And the values obtained from each of Nuselt convection which allow to know the rate of heat transfer in the cavity.Finally we find that there is a significant influence on the position of the fan on the heat transfer (Nusselt evolution) for values of Reynolds studied and for low values of Richardson handed this influence is negligible for high values of the latter.

Keywords: thermal transfer, mixed convection, square cavity, finite volume method

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1263 A Comparative Study on ANN, ANFIS and SVM Methods for Computing Resonant Frequency of A-Shaped Compact Microstrip Antennas

Authors: Ahmet Kayabasi, Ali Akdagli

Abstract:

In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

Procedia PDF Downloads 425
1262 The Optimum Mel-Frequency Cepstral Coefficients (MFCCs) Contribution to Iranian Traditional Music Genre Classification by Instrumental Features

Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

Abstract:

An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

Procedia PDF Downloads 426
1261 Evaluation of the Self-Organizing Map and the Adaptive Neuro-Fuzzy Inference System Machine Learning Techniques for the Estimation of Crop Water Stress Index of Wheat under Varying Application of Irrigation Water Levels for Efficient Irrigation Scheduling

Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

Abstract:

The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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1260 Neutral Sugars in Two-Step Hydrolysis of Laurel-Leaved and Cryptomeria japonica Forests

Authors: Ayuko Itsuki, Sachiyo Aburatani

Abstract:

Soil neutral sugar contents in Kasuga-yama Hill Primeval Forest, which is a World Heritage Site in Nara, Japan consisting of lowland laurel-leaved forest where natural conditions have been preserved for more than 1,000 years, were examined using the two-step hydrolysis to clarify the source of the neutral sugar and relations with the neutral sugar constituted the soil organic matter and the microbial biomass. Samples were selected from the soil (L, F, H and A horizons) surrounding laurel-leaved (BB-1) and Carpinus japonica (BB-2 and PW) trees for analysis. The neutral sugars were one factor of increasing the fungal and bacterial biomass in the laurel-leaved forest soil (BB-1). The more neutral sugar contents in the Cryptomeria japonica forest soil (PW) contributed to the growth of the bacteria and fungi than those of in the Cryptomeria japonica forest soil (BB-2). The neutral sugars had higher correlation with the numbers of bacteria and fungi counted by the dilution plate count method than by the direct microscopic count method. The numbers of fungi had higher correlation with those of bacteria by the dilution plate method.

Keywords: forest soil, neutral sugars, soil organic matter, two-step hydrolysis

Procedia PDF Downloads 245
1259 Experimental Study of LPG Diffusion Flame at Elevated Preheated Air Temperatures

Authors: Ahmed A. El-Kafy Amer, H. M. Gad, A. I. Ibrahim, S. I. Abdel-Mageed, T. M. Farag

Abstract:

This paper represents an experimental study of LPG diffusion flame at elevated air preheated temperatures. The flame is stabilized in a vertical water-cooled combustor by using air swirler. An experimental test rig was designed to investigate the different operating conditions. The burner head is designed so that the LPG fuel issued centrally and surrounded by the swirling air issues from an air swirler. There are three air swirlers having the same dimensions but having different blade angles to give different swirl numbers of 0.5, 0.87 and 1.5. The combustion air was heated electrically before entering the combustor up to a temperature about 500 K. Three air to fuel mass ratios of 30, 40 and 50 were also studied. The effect of air preheated temperature, swirl number and air to fuel mass ratios on the temperature maps, visible flame length, high temperature region (size) and exhaust species concentrations are studied. Some results show that as the air preheated temperature increases, the volume of high temperature region also increased but the flame length decreased. Increasing the air preheated temperature, EINOx, EICO2 and EIO2 increased, while EICO decreased. Increasing the air preheated temperature from 300 to 500 K, for all air swirl numbers used, the highest increase in EINOx, EICO2 and EIO2 are 141, 4 and 65%, respectively.

Keywords: air preheated temperature, air swirler, flame length, emission index

Procedia PDF Downloads 466
1258 Remote Assessment and Change Detection of GreenLAI of Cotton Crop Using Different Vegetation Indices

Authors: Ganesh B. Shinde, Vijaya B. Musande

Abstract:

Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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1257 Abundance and Diversity of Fruit Flies (Tephritidae: Diptera) In Citrus Orchards in Sindhuli, Nepal

Authors: Debraj Adhikari, Resham Bahadur Thapa, Samudra Lal Joshi, Jason Jinping Du, Sundar Tiwari

Abstract:

The purpose of this study was to keep a record of fruit fly species (Tephritidae: Diptera) in the sweet orange orchards of Sindhuli district, Nepal. Male fruit fly species were trapped and collected fortnightly using para-pheromone lures (methyl eugenol and cue lure) in Steiner traps at 25 orchards starting in March 2019 and continuing until February 2021. During the monitoring period, there was a significant variation in the occurrence of the fruit fly species. Fruit flies were captured in greater numbers during warm and rainy months (June, July, August, September) than during dry and winter months (December, January, February). Higher numbers of fruit flies were trapped in methyl eugenol than cue lure traps. Bactrocera dorsalis, B. zonata were major fruit fly species trapped in the methyl eugenol trap. Whereas, Zeugodacus tau, Z. cucurbitae, Z. scutellaris, and Dacus longicornis were major fruit fly species trapped in the cue lure trap. The findings of this study could be used to develop a long-term pest management strategy for the agro-ecological system.

Keywords: bactrocera, cue lure, methyl eugenol, monitoring, zeugodacus

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1256 Reliability Analysis of a Life Support System in a Public Aquarium

Authors: Mehmet Savsar

Abstract:

Complex Life Support Systems (LSS) are used in all large commercial and public aquariums in order to keep the fish alive. Reliabilities of individual equipment, as well as the complete system, are extremely important and critical since the life and safety of important fish depend on these life support systems. Failure of some critical device or equipment, which do not have redundancy, results in negative consequences and affects life support as a whole. In this paper, we have considered a life support system in a large public aquarium in Kuwait Scientific Center and presented a procedure and analysis to show how the reliability of such systems can be estimated by using appropriate tools and collected data. We have also proposed possible improvements for systems reliability. In particular, addition of parallel components and spare parts are considered and the numbers of spare parts needed for each component to achieve a required reliability during specified lead time are calculated. The results show that significant improvements in system reliability can be achieved by operating some LSS components in parallel and having certain numbers of spares available in the spare parts inventories. The procedures and the results presented in this paper are expected to be useful for aquarium engineers and maintenance managers dealing with LSS.

Keywords: life support systems, aquariums, reliability, failures, availability, spare parts

Procedia PDF Downloads 265
1255 A Framework for the Evaluation of Infrastructures’ Serviceability

Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

Abstract:

In 1994, Korea experienced a national tragedy of Seongsu Bridge collapse. The accident was severe enough to alert governmental officers to the problem of existing management policy for national infrastructures. As a result, government legislated the ‘Guidelines for the safety inspection and test of infrastructure’ which have been utilized as the primary tool to make decision for the maintenance and rehabilitation of infrastructure for last twenty years. Although it is clear that the guideline established a basics how to evaluate and manage the condition of infrastructures in systematic manner, it is equally clear that the guideline needs improvements in order to obtain reasonable investment decisions for budget allocation. Because its inspection and evaluation procedures mainly focused on the structural condition of infrastructures, it was hard to make decision when the infrastructures were in same level of structural condition. In addition, it did not properly reflect various aspects of infrastructures such as performance, public demand, capacity, etc., which were more valuable to public. Regardless of the importance, these factors were commonly neglected in governmental decision-making process, because there factors were somewhat subjective and difficult to quantify in rational manner. Thus, this study proposes a framework to properly evaluate the serviceability indicators using AHP and Fuzzy approach. The framework is expected to assist governmental agency in establishing effective investment strategies for budget planning.

Keywords: infrastructure, evaluation, serviceability, fuzzy

Procedia PDF Downloads 268
1254 Numerical Study of Rayleight Number and Eccentricity Effect on Free Convection Fluid Flow and Heat Transfer of Annulus

Authors: Ali Reza Tahavvor‚ Saeed Hosseini, Behnam Amiri

Abstract:

Concentric and eccentric annulus is used frequently in technical and industrial applications such as nuclear reactors, thermal storage system and etc. In this paper, computational fluid dynamics (CFD) is used to investigate two dimensional free convection of laminar flow in annulus with isotherm cylinders surface and cooler inner surface. Problem studied in thirty different cases. Due to natural convection continuity and momentum equations are coupled and must be solved simultaneously. Finite volume method is used for solving governing equations. The purpose was to obtain the eccentricity effect on Nusselt number in different Rayleight numbers, so streamlines and temperature fields must be determined. Results shown that the highest Nusselt number values occurs in degree of eccentricity equal to 0.5 upward for inner cylinder and degree of eccentricity equal to 0.3 upward for outer cylinder. Side eccentricity reduces the outer cylinder Nusselt number but increases inner cylinder Nusselt number. The trend in variation of Nusselt number with respect to eccentricity remain similar in different Rayleight numbers. Correlations are included to calculate the Nusselt number of the cylinders.

Keywords: natural convection, concentric, eccentric, Nusselt number, annulus

Procedia PDF Downloads 348